Theoretical Neuroscience

2026-09-18-int
Modelling working memory for neuroscience
2026-09-18 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Project
Working Memory in SNNs
Learning Working Memory in Recurrent Spiking Neural Networks Using Heterogeneous Delays
2026-04-16 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Project
2026-03-05-ue-natural-cognition
Artificial neural networks and machine learning applied to the understanding of biological vision
2026-03-05 Behavioural Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Artificial neural networks and machine learning applied to the understanding of biological vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2026-03-05 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Foveated Retinotopy Improves Classification and Localization in CNNs
Foveated Retinotopy in CNNs. We represent Left an input image and how it is transformed by foveated retinotopy. We show below a …
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Foveated Retinotopy Improves Classification and Localization in CNNs
2026-02-10-biomplus
Recréer des réseaux neuronaux pour améliorer la compréhension de notre cerveau.
2026-02-10 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
2026-02-03-ai-and-neuroscience-day
Al for visual processing and energy-efficient algorithms.
2026-02-03 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
2026-01-29-emergences
Sparse representations in biological vision applied to the effciency of machine learning.
2026-01-29 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
2025-10-16-flash-lag-effect
Suresh Krishna’s lab meeting
2025-10-16 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Mislocalization by Design: The Flash-Lag Effect as Prediction
Why do we sometimes misjudge where visual objects are? This talk explores how predictive processing may cause systematic perceptual …
2025-10-16 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Foveal Retinotopy and Dual Pathways: A Computational Model for Active Visual Search
Abstract This thesis investigates visual search through the lens of the dual visual pathways found in biological systems : the ventral …
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Soutenance de Jean-Nicolas Jérémie "Foveal Retinotopy and Dual Pathways: A Computational Model for Active Visual Search"
Jean-Nicolas Jérémie soutiendra publiquement ses travaux de thèse intitulés: Foveal Retinotopy and Dual Pathways: A Computational Model …
2025-10-10 4 min read Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
Soutenance de Jean-Nicolas Jérémie "Foveal Retinotopy and Dual Pathways: A Computational Model for Active Visual Search"
DynTex: A Real-Time Generative Model of Dynamic Naturalistic Luminance Textures
The visual systems of animals work in diverse and constantly changing environments where organism survival requires effective senses. …
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DynTex: A Real-Time Generative Model of Dynamic Naturalistic Luminance Textures
Artificial neural networks and machine learning applied to the understanding of biological vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Last updated on 2025-05-26 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Artificial neural networks and machine learning applied to the understanding of biological vision
2025-05-26-master-m-4-nc
Artificial neural networks and machine learning applied to the understanding of biological vision
2025-05-26 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
2025-03-11-phd-program-sparse-representations
Sparse representations in machine learning applied to the understanding of biological vision
2025-03-11 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
2025-02-14-supaero
Qu’est-ce que les Neurosciences peuvent apporter à l’Intelligence Artificielle ?
2025-02-14 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Project
2025-02-11-neuromath
When Cortical Neurons Talk Sideways: Beyond Feedforward Visual Processing
2025-02-11 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Project
Integrating the What and Where Visual Pathways to Improve CNN Categorisation
Convolutional Neural Networks (CNNs) have been widely used for categorisation tasks over the past decades. Many studies have attempted …
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Integrating the What and Where Visual Pathways to Improve CNN Categorisation
2024-09-09-agileneurobot-anr
Robots aériens agiles bio-mimetiques pour le vol en conditions réelles: Enjeux pour l’IA embarqué
2024-09-09 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Kernel Heterogeneity Improves Sparseness of Natural Images Representations
Both biological and artificial neural networks inherently balance their performance with their operational cost, which balances their …
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Self-Supervised Learning of Spiking Motifs in Neurobiological Data
Timing is essential for neural processing, but evidence for such temporal precision is still lacking. We have developed a theoretical …
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Self-Supervised Learning of Spiking Motifs in Neurobiological Data
Artificial neural networks and machine learning applied to the understanding of biological vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Last updated on 2024-05-13 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Cite Project Slides URL
2024-05-13-master-m-4-nc
Artificial neural networks and machine learning applied to the understanding of biological vision
2024-05-13 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
2024-04-10-ue-neurosciences-computationnelles
Artificial neural networks applied to the understanding of biological vision
2024-04-10 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
2024-04-17-phd-program-sparse-representations
Sparse representations in machine learning applied to the understanding of biological vision
2024-04-10 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
2024-03-27-emergences.md
Analyser de larges volumes de données neurobiologiques : modèles émergents bio-inspirés, a Seminar at the Emergences workshop, Autrans, France
2024-03-27 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
2024-02-05-udem.md
Neuromorphic models of vision, a Seminar at UdeM’s School of Optometry, Montréal
2024-02-05 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
2023-12-14-jraf.md
Event-based vision
2023-12-14 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
2023-11-07-snufa.md
Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network
2023-11-07 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
ANR MarmoCatch (2023-10/2029-04)
ANR MarmoCatch (2023-10/2029-04)
Biological Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
2023-09-27_icann.md
Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network
2023-09-27 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network
Recently, interest has grown in exploring the hypothesis that neural activity conveys information through precise spiking motifs. To …
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2023-09-08_fresnel.md
Event-based vision
2023-09-08 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
Cortical recurrence supports resilience to sensory variance in the primary visual cortex
Our daily endeavors occur in a complex visual environment, whose intrinsic variability challenges the way we integrate information to …
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Cortical recurrence supports resilience to sensory variance in the primary visual cortex
2023-05-10-phd-program_neurosciences-computationnelles.md
Interactions between machine learning, artificial neural networks and our understanding of biological vision
2023-05-10 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Convolutional Sparse Coding is improved by heterogeneous uncertainty modeling
Aleatoric uncertainty characterizes the variability of features found in natural images, and echoes the epistemic uncertainty …
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Postdoc position "Accurate detection of precise spiking motifs in neurobiological data"
THE POSITION HAS BEEN FILLED. Dear colleagues, Applications are welcome for a fully funded 18-month postdoctoral position for the …
2023-05-01 3 min read Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Postdoc position "Accurate detection of precise spiking motifs in neurobiological data"
Artificial neural networks and machine learning applied to the understanding of biological vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Last updated on 2023-03-29 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Cite Project Slides URL
2023-04-05-ue-neurosciences-computationnelles
Artificial neural networks and machine learning applied to the understanding of biological vision
2023-04-05 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Artificial neural networks and machine learning applied to the understanding of biological vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
Last updated on 2023-03-29 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Cite Project Slides URL
2023-04-03-master-m-4-nc
Artificial neural networks and machine learning applied to the understanding of biological vision
2023-04-03 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Ultra-Fast Image Categorization in biology and in neural models
Humans are able to robustly categorize images and can, for instance, detect the presence of an animal in a briefly flashed image in as …
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Ultra-Fast Image Categorization in biology and in neural models
Resilience to sensory uncertainty in the primary visual cortex
Our daily endeavors occur in a complex visual environment, whose intrinsic variability shapes the way we integrate information to make …
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2022-11-21_flash-lag-effect
[2022-11-21] Alex Reynaud’s lab meeting https://laurentperrinet.github.io/slides/2022-11-21_flash-lag-effect Only the speaker …
2022-11-21 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Polychronies (2022 / 2025)
A grant from the Ph.D. program in Integrative and Clinical Neuroscience (Post-doctoral position, 2022 / 2025).
Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Polychronies (2022 / 2025)
Pooling in a predictive model of V1 explains functional and structural diversity across species
Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high …
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Pooling in a predictive model of V1 explains functional and structural diversity across species
2022-03-23_UE-neurosciences-computationnelles
Réseaux de neurones artificiels et apprentissage machine appliqués à la compréhension de la vision
2022-03-23 Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Réseaux de neurones artificiels et apprentissage machine appliqués à la compréhension de la vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2022-03-23 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Statistics of the sparse representations of natural images
In most mammals, the primary visual cortex (V1) processes complex mixtures of orientations to construct an accurate neural …
Last updated on 2021-10-12 Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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Revisiting Horizontal Connectivity Rules in V1: From like-to-like towards like-to-All
Horizontal connections in the primary visual cortex of carnivores, ungulates and primates organize on a near-regular lattice. Given the …
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Soutenance de thèse Angelo Franciosini
Angelo Franciosini (Equipe NeOpTo) a soutenu sa thèse de doctorat intitulée: SDPC : a sparse and predictive model of the early visual system le Mardi 28 septembre 2021 à 13h à 15h30
2021-09-09 3 min read Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Soutenance de thèse Angelo Franciosini
Dynamical processing of orientation precision in the primary visual cortex
The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …
Last updated on 2021-07-12 NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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ANR ACES (2022/2026)
Assignment of credit and constraints on eye movement learning (2022/2026).
Behavioural Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
ANR ACES (2022/2026)
Pooling in a predictive model of V1 explains functional and structural diversity across species
In this talk, I will present the following paper : Pooling in a predictive model of V1 explains functional and structural diversity …
Last updated on 2021-06-14 NeuroAI & Machine Learning, Theoretical Neuroscience
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ANR RubinVase (2021/2024)
RedUndancy-free neuro-BIological desigN of Visual and Auditory SEnsing
NeuroAI & Machine Learning, Theoretical Neuroscience
ANR RubinVase (2021/2024)
Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to …
PDF Cite DOI Code URL arXiv
Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
ANR AgileNeuRobot (2021/2025)
Robots aériens agiles bio-mimetiques pour le vol en conditions réelles
Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Slides
ANR AgileNeuRobot (2021/2025)
Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding
Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …
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Understanding natural vision using deep predictive coding
Building models which efficiently process images is a great source of inspiration to better understand the processes which underly our …
2020-09-25 Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
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Visual search as active inference
Visual search is an essential cognitive ability, offering a prototypical control problem to be addressed with Active Inference. Under a …
2020-09-14 NeuroAI & Machine Learning, Theoretical Neuroscience
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A dual foveal-peripheral visual processing model implements efficient saccade selection
In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large …
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From the retina to action: Understanding visual processing
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2020-04-03 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding
Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …
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2020-03-13: Soutenance de thèse Victor Boutin
Victor Boutin (Equipe NeOpTo) a soutenu sa thèse de doctorat intitulée: Sparse deep predictive coding: a bio-inspired model of visual perception / Etude d’un algorithme hiérarchique et codage épars et prédictif : vers un modèle bio-inspiré de la perception visuelle le Vendredi 13 mars à 14h
Last updated on 2020-03-04 4 min read Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
2020-03-13: Soutenance de thèse Victor Boutin
Humans adapt their anticipatory eye movements to the volatility of visual motion properties
Humans are able to accurately track a moving object with a combination of saccades and smooth eye movements. These movements allow us …
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Humans adapt their anticipatory eye movements to the volatility of visual motion properties
From the retina to action: Dynamics of predictive processing in the visual system
Within the central nervous system, visual areas are essential in transforming the raw luminous signal into a representation which …
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From the retina to action: Dynamics of predictive processing in the visual system
Postdoc position on Visual computations using Spatio-temporal Diffusion Kernels and Traveling Waves
THE POSITION HAS BEEN FILLED. 18 month Post-doc position coordinated by Laurent Perrinet, supported by (INT, Marseille) and Yves Frégnac (UNIC-NeuroPSI, Gif).
2019-10-21 7 min read Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
Postdoc position on Visual computations using Spatio-temporal Diffusion Kernels and Traveling Waves
Learning where to look: a foveated visuomotor control model
In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large …
2019-07-15 Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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2019-05-20: Symposium on Active Inference at NeuroFrance 2019
We organized a Symposium at NeuroFrance 2019 entitled Active Inference: Bridging theoretical and experimental neurosciences. This is part of a series of theoretical neuroscience symposia organized in this international conference from the french Neursocience Society.
2019-05-20 7 min read Behavioural Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
SpikeAI: laureat du Défi Biomimétisme (2019)
Algorithmes événementiels d’Intelligence Artificielle / Event-Based Artificial Inteligence (2019).
Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
SpikeAI: laureat du Défi Biomimétisme (2019)
From the retina to action: Understanding visual processing
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2019-04-03 Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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From the retina to action: Predictive processing in the visual system
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2019-03-25 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to …
Cite URL arXiv
A hierarchical, multi-layer convolutional sparse coding algorithm based on predictive coding
Sparse coding holds the idea that signals can be concisely described as a linear mixture of few components (called atoms) picked from a …
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An adaptive homeostatic algorithm for the unsupervised learning of visual features
The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by large an …
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Orientation selectivity to synthetic natural patterns in a cortical-like model of the cat primary visual cortex
A key property of the neurons in the primary visual cortex (V1) is their selectivity to oriented stimuli in the visual field. …
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Temps et cerveau : comment notre perception nous fait voyager dans le temps
Lorsque nous observons un sablier, lorsque nous fixons notre regard sur les grains de sable qui tombent, nous avons le sentiment que le …
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Temps et cerveau : comment notre perception nous fait voyager dans le temps
Top-down connection in Hierarchical Sparse Coding
The brain has to solve inverse problems to correctly interpret sensory data and infer the set of causes that generated the sensory …
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Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on …
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Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
2018-04-05 : *Probabilities and Optimal Inference to understand the Brain* Workshop
We organize a Symposium at NeuroFrance 2019 entitled Active Inference: Bridging theoretical and experimental neurosciences. This is part of a series of theoretical neuroscience symposia organized in this international conference from the french Neursocience Society.
2018-04-05 1 min read Behavioural Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
2018-04-05 : *Probabilities and Optimal Inference to understand the Brain* Workshop
2018-03-26 : PhD Program: course in Computational Neuroscience
PhD Program: course in Computational Neuroscience.
2018-03-26 4 min read Behavioural Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
Project Project
A low-cost, accessible eye tracking framework
Recording eye movements is a technique that attracts an increasing number of scientists, but also in the general public. Indeed, this …
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Unsupervised Hierarchical Sparse Coding algorithm inspired by Biological Vision
The brain has to solve inverse problems to correctly interpret sensory data and infer the set of causes that generated the sensory …
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The flash-lag effect as a motion-based predictive shift
Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving …
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The flash-lag effect as a motion-based predictive shift
Efficient learning of sparse image representations using homeostatic regulation
One core advantage of sparse representations is the efficient coding of complex signals using compact codes. For instance, it allows …
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Efficient learning of sparse image representations using homeostatic regulation
One core advantage of sparse representations is the efficient coding of complex signals using compact codes. For instance, it allows …
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Modelling the dynamics of cognitive processes: from the Bayesian brain to particles
See a followup in Perrinet et al, 2012
2016-07-07 NeuroAI & Machine Learning, Theoretical Neuroscience
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ANR REM (2013/2016)
ANR REM : Renforcement et mouvements oculaires (2013/2016).
Behavioural Neuroscience, Theoretical Neuroscience
ANR REM (2013/2016)
Sparse Models for Computer Vision
The representation of images in the brain is known to be sparse. That is, as neural activity is recorded in a visual area, for instance …
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Sparse Models for Computer Vision
Anticipatory smooth eye movements and reinforcement
When an object is moving in the visual field, we are able to accurately track it with a combination of saccades and smooth eye …
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A Mathematical Account of Dynamic Texture Synthesis for Probing Visual Perception
See a followup in Jonathan Vacher, Andrew Isaac Meso, Laurent U Perrinet, Gabriel Peyré (2018). Bayesian Modeling of Motion Perception …
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Active inference, eye movements and oculomotor delays
This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. …
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Active inference, eye movements and oculomotor delays
Motion-based prediction model for flash lag effect
The flash lag effect (FLE) is a well known visual illusion that reveals the perceptual difference in position coding of moving and …
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Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network
As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing …
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WP5 - Demo 1.3 : Spiking model of motion-based prediction
The question how the visual system is able to create a coherent representation of a rapidly changing environment in the presence of …
2014-03-20 Behavioural Neuroscience, Biological Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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Advances in Texture Analysis for Emphysema Classification
In recent years, with the advent of High-resolution Computed Tomography (HRCT), there has been an increased interest for diagnosing …
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Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional …
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Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
Active inference, smooth pursuit and oculomotor delays
We consider the problem of sensorimotor delays in the optimal control of movement under uncertainty. Specifically, we consider axonal …
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Pursuing motion illusions: a realistic oculomotor framework for Bayesian inference
Accuracy in estimating an object’s global motion over time is not only affected by the noise in visual motion information but …
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